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gnu: Add r-mixomics.
* gnu/packages/bioconductor.scm (r-mixomics): New variable. Signed-off-by: Ricardo Wurmus <rekado@elephly.net>
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@ -4932,3 +4932,45 @@ (define-public r-flowsom
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"FlowSOM offers visualization options for cytometry data, by using
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self-organizing map clustering and minimal spanning trees.")
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(license license:gpl2+)))
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(define-public r-mixomics
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(package
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(name "r-mixomics")
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(version "6.8.0")
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(source
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(origin
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(method url-fetch)
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(uri (bioconductor-uri "mixOmics" version))
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(sha256
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(base32
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"1f08jx35amn3sfcmqb96mjxxsm6dnpzhff625z758x1992wj4zsk"))))
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(properties `((upstream-name . "mixOmics")))
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(build-system r-build-system)
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(propagated-inputs
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`(("r-corpcor" ,r-corpcor)
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("r-dplyr" ,r-dplyr)
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("r-ellipse" ,r-ellipse)
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("r-ggplot2" ,r-ggplot2)
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("r-gridextra" ,r-gridextra)
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("r-igraph" ,r-igraph)
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("r-lattice" ,r-lattice)
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("r-mass" ,r-mass)
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("r-matrixstats" ,r-matrixstats)
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("r-rarpack" ,r-rarpack)
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("r-rcolorbrewer" ,r-rcolorbrewer)
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("r-reshape2" ,r-reshape2)
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("r-tidyr" ,r-tidyr)))
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(home-page "http://www.mixOmics.org")
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(synopsis "Multivariate methods for exploration of biological datasets")
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(description
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"mixOmics offers a wide range of multivariate methods for the exploration
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and integration of biological datasets with a particular focus on variable
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selection. The package proposes several sparse multivariate models we have
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developed to identify the key variables that are highly correlated, and/or
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explain the biological outcome of interest. The data that can be analysed
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with mixOmics may come from high throughput sequencing technologies, such as
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omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but
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also beyond the realm of omics (e.g. spectral imaging). The methods
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implemented in mixOmics can also handle missing values without having to
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delete entire rows with missing data.")
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(license license:gpl2+)))
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